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Article
Publication date: 7 August 2024

Annie K. Lewis, Nicholas F. Taylor, Patrick W. Carney and Katherine E. Harding

Interventions that improve timely access to outpatient health services are essential in managing demand. This process evaluation aimed to describe the implementation, mechanism of…

Abstract

Purpose

Interventions that improve timely access to outpatient health services are essential in managing demand. This process evaluation aimed to describe the implementation, mechanism of impact and context of an intervention to reduce waiting for first appointments in an outpatient epilepsy clinic.

Design/methodology/approach

The UK Medical Research Council framework was used as the theoretical basis for a process evaluation alongside an intervention trial. The intervention, Specific Timely Appointments for Triage (STAT), is a data-driven approach that combines a one-off backlog reduction strategy with methods to balance supply and demand. A mixed methods process evaluation synthesised routinely collected quantitative and qualitative data, which were mapped to the domains of implementation, mechanisms of impact and contextual elements.

Findings

The principles of the STAT model were implemented as intended without adaptation. The STAT model reached all patients referred, including long waiters and was likely generalisable to other medical outpatient clinics. Mechanisms of impact were increased clinic capacity and elimination of unwanted variation. Contextual elements included the complexity of healthcare systems and the two-tier triage practice that contributes to prolonged waiting for patients classified as non-urgent.

Originality/value

This process evaluation shows how a data-driven strategy was applied in a medical outpatient setting to manage demand. Improving patient flow by reducing waiting in non-urgent, outpatient care is a complex problem. Understanding how and why interventions work is important for improved timeliness of care, and sustainability of public health services.

Details

Journal of Health Organization and Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1477-7266

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Year

Last 6 months (1)

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